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Approximations on Minimum Weight Pseudo-triangulation Problem Using Ant Colony Optimization Metaheuristic

机译:利用蚁群优化成群质训练的最小重量伪三角测量问题的近似值

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In this work, we consider the Minimum Weight Pseudo-Triangulation (MWPT) problem of a given set of $n$ points in the plane. Globally optimal pseudo-triangulations with respect to the $weight$, as optimization criteria, are difficult to be found by deterministic methods, since no polynomial algorithm is known. We show how the Ant Colony Optimization (ACO) metaheuristic can be used to find high quality pseudo-triangulations of minimum weight. We present the experimental and statistical study based on our own set of instances since no reference to benchmarks for these problems were found in the literature. Throughout the experimental evaluation, we appraise the ACO metaheuristic performance for MWPT problem.
机译:在这项工作中,我们考虑了飞机上给定的$ N $点的最低重量伪三角测量(MWPT)问题。通过确定性方法难以找到相对于$重量$的全球最佳伪三角形,因为确定性方法难以发现多项式算法。我们展示了如何使用蚂蚁殖民地优化(ACO)成群质型来查找最低重量的高质量伪三角形。我们基于我们自己的一组实例提出了实验和统计研究,因为在文献中没有参考这些问题的基准。在整个实验评估中,我们评估了MWPT问题的ACO成立性能。

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